This project is based on the data sources provided by [OurWorldInData project]: https://ourworldindata.org/nuclear-weapons.
Cited: Max Roser, Bastian Herre and Joe Hasell (2013) - “Nuclear Weapons”. Published online at OurWorldInData.org. Retrieved from: ‘https://ourworldindata.org/nuclear-weapons’ [Online Resource].
Nuclear Weapons Status data: I have used a data source (Nuclear Weapons Status) from Our World in Data to research the proliferation of nuclear weapons.
Here is a more specific link to where I found it: https://ourworldindata.org/nuclear-weapons#nuclear-powers-and-proliferation. See this for more information about the data on nuclear weapon proliferation. The information includes that the data source is based on Bleek (2017) and Nuclear Threat Initiative (2022). Under sources it is described that the data is published by Our World in Data, Bastian Herre.
Link to Bastians Herre’s Github: https://github.com/owid/notebooks/tree/main/BastianHerre/nuclear_weapons/OWID%20based%20on%20Bleek%20(2017)%2C%20Nuclear%20Threat%20Initiative%20(2022)%20nuclear%20weapons%20proliferation
Nuclear Weapons Testing data: The other data source (Nuclear Weapons Testing) used in this study is also provided by Our World In Data: https://ourworldindata.org/nuclear-weapons#nuclear-weapons-tests. This link provides more information specified about the data. This data source provides the number of nuclear weapons testing by country. The data is published by Arms Control Association. Here is a more specific link: https://www.armscontrol.org/factsheets/nucleartesttally.
This data can also be found on Bastian Herre’s Github: https://github.com/owid/notebooks/tree/main/BastianHerre/nuclear_weapons/Arms%20Control%20Association%20(2020)%20nuclear%20weapons%20tests
To make my visualization i need to install and use the library tidyverse and ggplot2.
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.3 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.3 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(ggplot2)
Next I read and view my data.
Nuclear_Weapons_Countries <- read.csv("data/country-position-nuclear-weapons.csv")
View(Nuclear_Weapons_Countries) # Checking the data
Nuclear_Weapons_Tests <- read.csv("data/number-of-nuclear-weapons-tests.csv")
View(Nuclear_Weapons_Tests) # Checking the data
head(Nuclear_Weapons_Countries)
## Entity Code Year nuclear_weapons_status
## 1 Abkhazia OWID_ABK 1938 0
## 2 Abkhazia OWID_ABK 1939 0
## 3 Abkhazia OWID_ABK 1940 0
## 4 Abkhazia OWID_ABK 1941 0
## 5 Abkhazia OWID_ABK 1942 0
## 6 Abkhazia OWID_ABK 1943 0
head(Nuclear_Weapons_Tests)
## Entity Code Year nuclear_weapons_tests
## 1 China CHN 1945 0
## 2 China CHN 1946 0
## 3 China CHN 1947 0
## 4 China CHN 1948 0
## 5 China CHN 1949 0
## 6 China CHN 1950 0
The data looks good for my purpose.
I will research which countries had nuclear weapons before the Cold War, during the Cold War and in the present. This way I can compare the development of nuclear weapons and how it has spread. Who has been and who is in possession of nuclear weapons? And what can be concluded from this?
The study of nuclear weapons status should be used to compare with the testing of nuclear weapons. This is to see if there is a correlation.
Nuclear_Weapons_Countries <- read.csv("data/country-position-nuclear-weapons.csv")
Here I filter my data so I can get a view on the year 1945.
Nuclear_Weapons_1945 <- read.csv("data/country-position-nuclear-weapons.csv") %>%
filter(Year == 1945)
I use ggplot to create a visualization with the data sorted to the year 1945, using geom_col to get the lines and adding labels and title.
ggplot(data = Nuclear_Weapons_1945, aes(x = Entity, y = nuclear_weapons_status)) +
geom_col() +
labs(title = "Nuclear Weapons Status in 1945", x = "Country", y = "Nuclear Weapons Status") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This plot is a little confusing with so many countries with most of them with a score of 0, so I will look at the top 20 countries depending on the highest score and below. I will be looking at the countries scoring the number of 1, 2 or 3 in the year 1945, 1975 and 2020 below.
Sorted_data1 is arranged so the highest score comes first.
sorted_data1 <- Nuclear_Weapons_1945 %>%
arrange(desc(nuclear_weapons_status))
I select the 20 countries with the highest scores using my sorted data.
top_20_countries1945 <- head(sorted_data1, 20)
I use ggplot to make a visualization. I use geom_bar to make it with bar and making in the colour of skyblue. Adding labels and title with labs.
ggplot(data = top_20_countries1945, aes(x = reorder(Entity, -nuclear_weapons_status), y = nuclear_weapons_status)) +
geom_bar(stat = "identity", fill = "skyblue") +
labs(title = "Top 20 Countries with the Highest Nuclear Weapons Status (1945)",
x = "Country",
y = "Nuclear Weapons Status") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
In this visualization USA is the only country with nuclear weapons. The Soviet Union (Russia) and Great Britain wants to pursuit, France, Germany, Japan and Switzerland is considering in 1945.
The visualization I have created for the year 1945, I will create again for the year 1975 and 2020 below.
Nuclear_Weapons_Countries <- read.csv("data/country-position-nuclear-weapons.csv")
Nuclear_Weapons_1975 <- read.csv("data/country-position-nuclear-weapons.csv") %>%
filter(Year == 1975)
ggplot(data = Nuclear_Weapons_1975, aes(x = Entity, y = nuclear_weapons_status)) +
geom_col() +
labs(title = "Nuclear Weapons Status in 1975", x = "Country", y = "Nuclear Weapons Status") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
There is a significant difference from the visualization from 1945 to the visualization in 1975. This is also more clear in the top 20 countries I will investigate below.
sorted_data2 <- Nuclear_Weapons_1975 %>%
arrange(desc(nuclear_weapons_status))
top_20_countries1975 <- head(sorted_data2, 20)
ggplot(data = top_20_countries1975, aes(x = reorder(Entity, -nuclear_weapons_status), y = nuclear_weapons_status)) +
geom_bar(stat = "identity", fill = "skyblue") +
labs(title = "Top 20 Countries with the Highest Nuclear Weapons Status (1975)",
x = "Country",
y = "Nuclear Weapons Status") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This visualization shows that many more countries were considering, pursuing, or possessing nuclear weapons. The United States no longer had a monopoly on nuclear weapons. The Soviet Union (Russia), Britain, China, France, and Israel now also possessed nuclear weapons.
The next year I will Inspect is 2020. I am doing the same as above.
Nuclear_Weapons_Countries <- read.csv("data/country-position-nuclear-weapons.csv")
Nuclear_Weapons_2020 <- read.csv("data/country-position-nuclear-weapons.csv") %>%
filter(Year == 2020)
ggplot(data = Nuclear_Weapons_2020, aes(x = Entity, y = nuclear_weapons_status)) +
geom_col() +
labs(title = "Nuclear Weapons Status in 2020", x = "Country", y = "Nuclear Weapons Status") +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This visualization shows that more countries are possessing nuclear weapons in 2020 than in 1945 and 1975. Pakistan, North Korea, and India are now also possessing them. The difference is that most countries are no longer considering or pursuing nuclear weapons. This is more clear in the top 20 countries created below.
sorted_data3 <- Nuclear_Weapons_2020 %>%
arrange(desc(nuclear_weapons_status))
top_20_countries2020 <- head(sorted_data3, 20)
ggplot(data = top_20_countries2020, aes(x = reorder(Entity, -nuclear_weapons_status), y = nuclear_weapons_status)) +
geom_bar(stat = "identity", fill = "skyblue") +
labs(title = "Top 20 Countries with the Highest Nuclear Weapons Status (2020)",
x = "Country",
y = "Nuclear Weapons Status") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
As described above more countries posses nuclear weapons in 2020, but not as many as in 1945 and 1975 are now pursuing or considering possesing nuclear weapons.
There has been an evolution over time. The US has gone from having a monopoly on nuclear weapons in 1945 to more countries possessing them in 2020. The desire to possess nuclear weapons has decreased from 1975 to 2020, which probably indicates a disarmament and détente after the end of the Cold War, which partially ended with the fall of the Berlin Wall in 1989 and finally with the collapse of the Soviet Union in 1991.
Something else I wanted to look into is the testing of Nuclear Weapons, to see if there is a correlation with nuclear weapons status.
I begin with reading and inspecting the data.
Nuclear_Weapons_Tests <- read.csv("data/number-of-nuclear-weapons-tests.csv")
head(Nuclear_Weapons_Tests)
## Entity Code Year nuclear_weapons_tests
## 1 China CHN 1945 0
## 2 China CHN 1946 0
## 3 China CHN 1947 0
## 4 China CHN 1948 0
## 5 China CHN 1949 0
## 6 China CHN 1950 0
Next, I create a visualization showing testing of nuclear weapons over time from 1945 until 2019.
ggplot(data = Nuclear_Weapons_Tests, aes(x = Year, y = nuclear_weapons_tests)) +
geom_col() +
labs(title = "Nuclear Weapons Tests Over Time", x = "Year", y = "Nuclear Weapons Tests") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This visualisation shows that during the Cold War there was alot of testing with Nuclear Weapons. After the Cold War testing has not been so frequent.
I would like to find out which countries tested the most. To do that I switch out the variable ‘Year’ with ‘Enity’.
ggplot(data = Nuclear_Weapons_Tests, aes(x = Entity, y = nuclear_weapons_tests, color = Entity)) +
geom_line() +
labs(title = "Nuclear Weapons Tests Countries (1945 - 2019)", x = "Country", y = "Nuclear Weapons Tests") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This visualisation shows that the United States and Russia was the two countries who tested the most over time. Now i would like to see this visualiztion, but only in the year of 1975 - in the middle of The Cold War.
Filtering the data to get the data only from the year 1975.
Nuclear_Weapons_Tests1975 <- read.csv("data/number-of-nuclear-weapons-tests.csv") %>%
filter(Year == 1975)
ggplot(data = Nuclear_Weapons_Tests1975, aes(x = Entity, y = nuclear_weapons_tests, color = Entity)) +
geom_col() +
labs(title = "Nuclear Weapons Tests Countries (1975)", x = "Country", y = "Nuclear Weapons Tests") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
The two superpowers during the Cold War, The Soviet Union (Russia) and USA, are the two countries testing the most in 1975. Im a little curious about which countries tested in 2010 after The Cold War. The next visualization will show this. Then I can compare it with the one from 1975.
Filtering to get the data only from 2010.
Nuclear_Weapons_Tests2010 <- read.csv("data/number-of-nuclear-weapons-tests.csv") %>%
filter(Year == 2010)
ggplot(data = Nuclear_Weapons_Tests2010, aes(x = Entity, y = nuclear_weapons_tests, color = Entity)) +
geom_col() +
labs(title = "Nuclear Weapons Tests Countries (2010)", x = "Country", y = "Nuclear Weapons Tests") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
This is interesting. North Korea is the only country testing in 2010. The two superpowers, Russia and USA, is no longer during tests. This visualization shows some of the consequences of nuclear weapons. Nuclear weapons are spreading to other countries after the Cold War. Other countries stopped testing nuclear weapons after the Cold War during deténte and disarmament. But why is North Korea testing in 2010, and what are their intentions? I will not be researching this in this project.
I wanted to make my visuliazation more detailed and make it easier to see countries numbers of tests in a specific year. So I combined what I did in the visualizations above. I have used plotly to make a more detailed visuliazation, which can combine my visualization from above. This makes it easier for researching. The countries is colored and when you put the mouse on the little markers/dots you can see how many times that a specific country tested in a specific year.
To create a visualization I need to install and load packages. I used plotly and dplyr.
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
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## layout
library(dplyr)
I begin with loading the data and giving it a new name.
Nuclear_Weapons_Tests_Plotly <- read.csv("data/number-of-nuclear-weapons-tests.csv")
Next, I create a plotly visualization giving and naming the x and y axises, giving it color, type and mode.
plotly_Nuclear_Weapons <- Nuclear_Weapons_Tests_Plotly %>%
plot_ly(x = ~Year, y = ~nuclear_weapons_tests, color = ~Entity, type = 'scatter', mode = 'lines+markers')
Giving my visualization labels and title.
plotly_Nuclear_Weapons%>%
layout(title = "Nuclear Weapons Tests Over Time") %>%
layout(xaxis = list(title = "Year")) %>%
layout(yaxis = list(title = "Nuclear Weapons Tests"))
This is my result.
plotly_Nuclear_Weapons
Nuclear weapons were developed in the mid-19th century. The United States was the first to possess nuclear weapons. However, several countries followed in their footsteps. In my project it is clear there is a significant development from 1945 to 2020 in the proliferation of nuclear weapons. My results show an interest in developing and testing nuclear weapons throughout the Cold War. After the collapse of the Soviet Union in 1991 it is clear from my research that testing and the desire to possess nuclear weapons has decreased. However, there are still more countries that possess nuclear weapons today. Disarmament and political efforts to reduce the threat of nuclear weapons are clearly visible in the visualizations. However, this does not mean that the threat of nuclear weapons today is not as great as during the Cold War.